Land cover mapping based on random forest classification of multitemporal spectral and thermal images

Thematic mapping of complex landscapes, with various phenological patterns from satellite imagery, is a particularly challenging task. However, supplementary information, such as multitemporal data and/or land surface temperature (LST), has the potential to improve the land cover classification accuracy and efficiency. In this paper, in order to map land covers, we evaluated the potential of multitemporal Landsat 8’s spectral and thermal imageries using a random forest (RF) classifier. We used a grid search approach based on the out-of-bag (OOB) estimate of error to optimize the RF parameters. Four different scenarios were considered in this research: (1) RF classification of multitemporal spectral images, (2) RF classification of multitemporal LST images, (3) RF classification of all multitemporal LST and spectral images, and (4) RF classification of selected important or optimum features. The study area in this research was Naghadeh city and its surrounding region, located in West Azerbaijan Province, northwest of Iran. The overall accuracies of first, second, third, and fourth scenarios were equal to 86.48, 82.26, 90.63, and 91.82 %, respectively. The quantitative assessments of the results demonstrated that the most important or optimum features increase the class separability, while the spectral and thermal features produced a more moderate increase in the land cover mapping accuracy. In addition, the contribution of the multitemporal thermal information led to a considerable increase in the user and producer accuracies of classes with a rapid temporal change behavior, such as crops and vegetation.     

Effect of Thermo-Mechanical Degradation of Polypropylene on Hygroscopic Characteristics of Wood Flour-Polypropylene Composites

In this research, the influence of thermo-mechanical degradation of polypropylene (PP) on water absorption and thickness swelling of beech wood flour–PP composites were studied. For this purpose, a virgin PP was thermo-mechanically degraded by two times extrusion under controlled conditions. The results showed that the melt flow index, water absorption and thickness swelling of PP significantly increase by extrusion and re-extrusion. The virgin PP and degraded polypropylene were compounded with wood flour (at 60% by weight wood flour loading) in a counter-rotating twin-screw extruder in presence or absence of MAPP to produce wood flour–PP composites. From the results, the composites containing recycled PP exhibited higher water absorption and thickness swelling. The use of MAPP decreased water absorption and thickness swelling in composites made of virgin or recycled PP.     

Assessment of the Effectiveness of Protected Areas Management in Iran: Case Study in Khojir National Park

The requirement to assess the management effectiveness (ME) in protected areas (PAs) is increasing around the world to help improve management and accountability. An evaluation of ME for Khojir National Park (KNP), one of the Iran’s oldest PAs, was conducted using a multi-method approach that consisted of structured interviews, open interviews, and site visits. This was the first ME evaluation in Iran. The structured interview was based on the management effectiveness tracking tool methodology. KNP received an average score of 43 %, which is lower than the global average, illustrating that its general management was in the low-intermediate level. The indices of legal status, resource inventory, planning for land and water use, regulations, and objectives received the highest average scores, whereas education and awareness, community co-management, regular work plan, boundary demarcation, visitor facilities, budget sources, staff training, protection systems, and management plan received the lowest ones. The management system of KNP was generally established, but many problems of the management still need to be resolved. To improve ME, some countermeasures should be taken, such as increasing funding, strengthening capacity building, planning, and adaptive management, and implementing community participation.     

Effects of heterogeneities on capillary pressure-saturation-relative permeability relationships

In theories of multiphase flow through porous media, capillary pressure-saturation and relative permeability-saturation curves are assumed to be intrinsic properties of the medium. Moreover, relative permeability is assumed to be a scalar property. However, numerous theoretical and experimental works have shown that these basic assumptions may not be valid. For example, relative permeability is known to be affected by the flow velocity (or pressure gradient) at which the measurements are carried out. In this article, it is suggested that the nonuniqueness of capillary pressure-relative permeability-saturation relationships is due to the presence of microheterogeneities within a laboratory sample. In order to investigate this hypothesis, a large number of "numerical experiments" are carried out. A numerical multiphase flow model is used to simulate the procedures that are commonly used in the laboratory for the measurement of capillary pressure and relative permeability curves. The dimensions of the simulation domain are similar to those of a typical laboratory sample (a few centimeters in each direction). Various combinations of boundary conditions and soil heterogeneity are simulated and average capillary pressure, saturation, and relative permeability for the "soil sample" are obtained. It is found that the irreducible water saturation is a function of the capillary number; the smaller the capillary number, the larger the irreducible water saturation. Both drainage and imbibition capillary pressure curves are found to be strongly affected by heterogeneities and boundary conditions. Relative permeability is also found to be affected by the boundary conditions; this is especially true about the nonaqueous phase permeability. Our results reveal that there is much need for laboratory experiments aimed at investigating the interplay of boundary conditions and microheterogeneities and their effect on capillary pressure and relative permeability.     

Investigating the performance of aerobic,semi-aerobic,and anaerobic bioreactor landfills for MSW management in developing countries

Three different laboratory bioreactors, each duplicated, with dimensions 0.5 × 0.5 × 1 m were set up and monitored for 160 days. Municipal Solid Wastes with an organic content of ~80 % and a density of 550 kg/m³ were placed in bioreactors. Fresh leachate collected from waste collection vehicles was used with a recirculation rate of 28 L/day. Aerobic bioreactors were aerated at a rate of 0.15–0.24 L/min/kg of waste. Almost the same level of treatment was observed in terms of chemical oxygen demand reduction of leachate, which was in the range of 91–93 %. However, for anaerobic bioreactor, it took almost twice the time, 160 vs. 76 days, to reach the same level of treatment and stabilization. The behavior of semi-aerobic bioreactor was somewhere between the aerobic and anaerobic ones. Total biogas production for anaerobic bioreactors was 90 L/kg of waste, which contained 57–63 % methane. Methane concentration measured in semi-aerobic bioreactor was below 5 %. The main advantage of aerobic bioreactor was the fast rate of the process, while for semi-aerobic bioreactor, it was the elimination of the need for energy to maintain aerobic conditions, and for anaerobic bioreactor it was the production of biogas and potential energy recovery.     

The role of burnout syndrome as a mediator for the effect of psychosocial risk factors on the intensity of musculoskeletal disorders: a structural equation modeling approach

This study examined the hypothesis that burnout syndrome mediates effects of psychosocial risk factors and intensity of musculoskeletal disorders (MSDs) among hospital nurses. The sample was composed of 415 nurses from various wards across five hospitals of Iran's Hamedan University of Medical Sciences. Data were collected through three questionnaires: job content questionnaire, Maslach burnout inventory and visual analogue scale. Results of structural equation modeling with a mediating effect showed that psychosocial risk factors were significantly related to changes in burnout, which in turn affects intensity of MSDs.     

Epidemiological and biomechanical evaluation of airline baggage handling

Objectives. Musculoskeletal disorders (MSDs) are prevalent among airline baggage handlers due to manual materials handling. In this study, the Nordic musculoskeletal questionnaire (NMQ), the revised National Institute for Occupational Safety and Health (NIOSH) lifting equation, and the University of Michigan 3D Static Strength Prediction Program? (3DSSPP) were used to analyze MSDs among baggage handlers. Methods. The NMQ was filled out by 209 baggage handlers and 46 arbitrarily selected baggage handlers were evaluated using the NIOSH method and 3DSSPP. Results. The obtained results showed that the most common MSDs occurred in the lower back region. The next risky regions included knees, neck, and upper back, respectively. The NIOSH results confirmed that the subjects lifted loads heavier than the permitted limit and their lifting postures were inappropriate. The results of the 3DSSPP also indicated that compression forces exceeded the NIOSH limit in these awkward postures. Conclusions. Relying on this study, holding compulsory ergonomic lifting training courses could be proposed for workers and regulations adjusting an upper limit for maximum baggage weight must be also enacted in order to improve occupational health and prevent the prevalence of increasing MSDs.     

Stormwater Control Measures for Runoff and Water Quality Management in Urban Landscapes

This study develops and tests a novel optimization method for optimally selecting and sizing stormwater control measures (SCMs) in urban landscapes for selected design storms. The developed methodology yields SCMs that capture and retain stormwater via onsite percolation, remove stormwater pollutants, and minimize stormwater control expenditures. The resulting environmental optimization problem involves integer and real variables imbedded in an objective function that is subjected to multiple constraints. This study's methodology aims at practicality and ease of implementation in the solution of the SCM sizing and selection optimization problem while taking into account the main factors that govern stormwater management in urban landscapes. The near‐optimal global solution of the SCM selection and design problem is obtained with nonlinear programming and verified with the average of multiple solutions calculated with multiple runs of an optimization evolutionary algorithm. The developed methodology is illustrated with one stormwater project in the City of Los Angeles, California.     

LaSVM-based big data learning system for dynamic prediction of air pollution in Tehran

Due to critical impacts of air pollution, prediction and monitoring of air quality in urban areas are important tasks. However, because of the dynamic nature and high spatio-temporal variability, prediction of the air pollutant concentrations is a complex spatio-temporal problem. Distribution of pollutant concentration is influenced by various factors such as the historical pollution data and weather conditions. Conventional methods such as the support vector machine (SVM) or artificial neural networks (ANN) show some deficiencies when huge amount of streaming data have to be analyzed for urban air pollution prediction. In order to overcome the limitations of the conventional methods and improve the performance of urban air pollution prediction in Tehran, a spatio-temporal system is designed using a LaSVM-based online algorithm. Pollutant concentration and meteorological data along with geographical parameters are continually fed to the developed online forecasting system. Performance of the system is evaluated by comparing the prediction results of the Air Quality Index (AQI) with those of a traditional SVM algorithm. Results show an outstanding increase of speed by the online algorithm while preserving the accuracy of the SVM classifier. Comparison of the hourly predictions for next coming 24 h, with those of the measured pollution data in Tehran pollution monitoring stations shows an overall accuracy of 0.71, root mean square error of 0.54 and coefficient of determination of 0.81. These results are indicators of the practical usefulness of the online algorithm for real-time spatial and temporal prediction of the urban air quality.